Both Mitch Ratcliffe and Matthew Hurst have some very interesting thoughts on defining influence. In some of our work we have tried to explore what influence means on the Blogosphere and how can we measure it. We found that PageRank of the blog is definitely one of the contributing factors for measuring influence, and being authoritative ofcourse would mean that people are more likely to listen to you. But influence is not limited to authority alone. I like matthew Hurst’s suggestion of breaking influence into smaller, directly measurable components like:

Authority: the expertise level of the individual.

Credibility: the trust of the readers for the individual and the manner of presentation.

In addition to the above, I would like to point out that IMHO, this is just the beginning of the list. In coming up with the definition or modeling influence, we need to consider some of the following aspects:

Influence is topical: For example a blog like Daily Kos that is influential in politics is less likely to have an impact on the technology related blogs. Similarly, Techcrunch, an extremely popular technology blog might not be influential when it comes to politics.

Influence is polar: A community of “Ipod fans”, for example needs no convincing about the product. On the other hand an “influential” blogger talking negatively about your product might have a drastic impact. In some of the related work, we have participated in the TREC blog track’s opinion extraction task. We feel that opinions, biases and polarity of the links matter when measuring influence on the Blogosphere.

Influence is temporal: A blog’s influence on a topic might change with time. Tracking blogs over time also allows usto differentiate blogs that are influential versus something that is just briefly popular. For example, many thousands of sites linking to a â€˜Coke Mentosâ€™ video in one day indicates popularity. But thousands of links accumulated consistently over time by a blog indicate that it is influential.

In the end, we need some measures that are based on link count, traffic, readership (see also “feeds that matter“) etc. But we also need to consider more factors that make a blog “influential” and this would involve using a combination of graph, linguistic and temporal analysis. It might be hard to come up with an exact definition of influence, but the exciting thing is that there are a LOT of interesting challenges in this space!